Smart and Precision Agriculture (SPA) methods and technologies, such as autonomous robots, AI/ML, sensors, and actuators, enhance farming productivity by automating the retrieval of environmental parameters and the decision-making process, while Fog- and Edge-based paradigms enable more informed and responsive practices. Unmanned Aerial Vehicles (UAVs) can autonomously inspect crops and promptly cooperate with terrestrial vehicles to perform treatments, as recently demonstrated by the EU-funded COMP4DRONES (C4D) research project, focused on the provisioning of innovative UAV technologies for civilian applications. Modern companion-equipped UAV leverage Heterogeneous Systems-on-Chip (HeSoCs) to execute complex on-board tasks. HeSoCs generally combine a general-purpose, multi-core processor with a domain-specific accelerator-rich subsystem, massively integrating application-specific accelerators. Field Programmable Gate Array (FPGA) based HeSoCs are ideal fabrics to attain high performance and energy efficiency because of their massively parallel, deeply pipelined, non-Von-Neumann processing logic and custom memory hierarchies. Automated hardware-software co-design methodologies, e.g., FPGA overlays and toolflows, largely simplify the design phases, including the optimization of the accelerator interfaces, such as the merging of redundant components to reduce area usage. In this context, our contribution consists of a System-Level Design (SLD) methodology for the design of overlay-based UAV companion computers, including a modular and scalable accelerator-rich RISC-V HeSoC, a heterogeneous software stack and an automation toolchain to generate and integrate application-specific accelerators into our overlay. Our results show three optimized overlay variants targeting an UAV-based system employed in a SPA context. Experimental results denote improvements in performance and area usage, up to 18.5% on a FPGA-based HeSoC with respect to traditional design flows.
An FPGA-based accelerator design methodology for smart UAVs in precision agriculture: A case study
Palumbo, Francesca;
In corso di stampa
Abstract
Smart and Precision Agriculture (SPA) methods and technologies, such as autonomous robots, AI/ML, sensors, and actuators, enhance farming productivity by automating the retrieval of environmental parameters and the decision-making process, while Fog- and Edge-based paradigms enable more informed and responsive practices. Unmanned Aerial Vehicles (UAVs) can autonomously inspect crops and promptly cooperate with terrestrial vehicles to perform treatments, as recently demonstrated by the EU-funded COMP4DRONES (C4D) research project, focused on the provisioning of innovative UAV technologies for civilian applications. Modern companion-equipped UAV leverage Heterogeneous Systems-on-Chip (HeSoCs) to execute complex on-board tasks. HeSoCs generally combine a general-purpose, multi-core processor with a domain-specific accelerator-rich subsystem, massively integrating application-specific accelerators. Field Programmable Gate Array (FPGA) based HeSoCs are ideal fabrics to attain high performance and energy efficiency because of their massively parallel, deeply pipelined, non-Von-Neumann processing logic and custom memory hierarchies. Automated hardware-software co-design methodologies, e.g., FPGA overlays and toolflows, largely simplify the design phases, including the optimization of the accelerator interfaces, such as the merging of redundant components to reduce area usage. In this context, our contribution consists of a System-Level Design (SLD) methodology for the design of overlay-based UAV companion computers, including a modular and scalable accelerator-rich RISC-V HeSoC, a heterogeneous software stack and an automation toolchain to generate and integrate application-specific accelerators into our overlay. Our results show three optimized overlay variants targeting an UAV-based system employed in a SPA context. Experimental results denote improvements in performance and area usage, up to 18.5% on a FPGA-based HeSoC with respect to traditional design flows.
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